Webcast with Dr. Sonia Gallegos

On March 4 Dr. Sonia C. Gallegos presented a webcast from the campus of Elizabeth City State University on her research and development of optical models for the Yellow Sea.

Sonia Gallegos holds a Ph.D. degree in Oceanography from Texas A & M University and is currently a Principal Investigator with the Naval Research Laboratory at Stennis Space Center in Mississippi. She has over 20 years of experience in Remote Sensing of the earth and oceans. She started her remote sensing career as a physical scientist with NOAA/NESDIS at the Johnson Space Center in Texas and Washington. At NOAA, her work included the development of visible and near-infrared algorithms for land and water applications. In 1986 she moved to the University of Texas at Austin - Center for Space Research where she worked in developing algorithms for red tide and oil detection from visible and infrared sensors. In 1990 she became part of Naval Research Laboratory Remote Sensing Applications Branch. At NRL she has developed algorithms for cloud detection and masking as well as a number of applications for naval tactical operations. She currently works in the Optics Branch of NRL where she develops models that integrate remote sensing measurements, in-situ data and products from dynamic models that allow the estimation of inherent optical properties from the surface to the bottom of the ocean.

Abstract -
A Real Time Remote Sensing Algorithm for Spectral Attenuation Coefficient
A real-time remote sensing algorithm was developed to transform water-leaving radiance from ocean color satellite sensors (SeaWiFS, MODIS and NEMO) into hourly three-dimensional predictive maps of spectral attenuation coefficient (water clarity). This algorithm or model merges optical and environmental parameters via neuromorphic algorithms. The training parameters include (1) current velocity and direction from Navy oceanographic models, (2) bathymetry and sediment type, (3) sigma-t, (4) in situ measurements of Inherent and Apparent Optical Properties of the water and, (5) water leaving radiance from satellites. The estimations of the model require oceanographic data, exclusively. The model runs concurrently with two Navy oceanographic models. These are a tidal assimilation model based on shallow water equations and a statistical model (MODAS) which produces salinity and temperature worldwide. This is the first environmental model in which oceanographic parameters are used to accurately predict optical properties of the water. The algorithm relies on databases from Navy archives, and on optical and environmental data collected in cruises off the coast of Korea in the Yellow Sea. RMSE between estimated and measured values ranges from .02 m-1 at the surface to 1.2 m-1 at 60m.

Dr. Linda B. Hayden
Elizabeth City State University

Dr. Sonia C. Gallegos
Naval Research Laboratory
at Stennis Space Center